Networks, such as the Internet, have become an increasingly important part of our everyday lives. Millions of people now access the Internet on a daily basis to shop for goods and services, obtain information of interest (e.g., movie listings, news, etc.), and communicate with friends, family, and co-workers (e.g., via e-mail or instant messaging).
Currently, when a person wishes to purchase a product or simply find information on the Internet, the person enters into his/her web browser a Uniform Resource Locator (URL) pertaining to a web site of interest in order to access that particular web site. The person then determines whether the information of interest is available at that particular web site.
For example, suppose a person wishes to obtain the latest news regarding a particular topic via the Internet. The person accesses a web site that includes a conventional search engine. The person enters one or more terms relating to the topic of interest, such as “Iraq,” into the search engine to attempt to locate a news source that has published an article relating to the topic. Using a search engine in this manner to locate individual web sites that provide news articles relating to the desired topic often results in a ranked list of hundreds or even thousands of “hits,” where each hit may correspond to a web page that relates to the search term(s).
While each of the hits in the ranked list may relate to the desired topic, the news sources associated with these hits, however, may not be of uniform quality. For example, CNN and BBC are widely regarded as high quality sources of accuracy of reporting, professionalism in writing, etc., while local news sources, such as hometown news sources, may be of lower quality.
Therefore, there exists a need for systems and methods for improving the ranking of news articles based on the quality of the news source with which the articles are associated.